DARPA funds graph analytics processor
Last week I posted a bunch of links pointing towards quantum computing. However, there are also other compute initiatives which also offer significant potential for “redefining intractable” for problems such as graph comparison, for example, DARPA’s HIVE which aims to create a 1000x improvement in processing speed (and at much lower power) on this problem. Write-up on EE Times of the DARPA HIVE program here.
Exploring long short-term memory networks
Nice explainer on LSTMs by Edwin Chen: “The first time I learned about LSTMs, my eyes glazed over. Not in a good, jelly donut kind of way. It turns out LSTMs are a fairly simple extension to neural networks, and they’re behind a lot of the amazing achievements deep learning has made in the past few years.” (Long, detailed and interesting blog post, but even if you just read the first few page scrolls still quite worthwhile for the intuition of the value and function of LSTMs.)
FairML: Auditing black box predictive models
Machine learning models are used for important decisions like determining who has access to bail. The aim is to increase efficiency and spot patterns in data that humans would otherwise miss. But how do we know if a machine learning model is fair? And what does fairness in machine learning mean? Paper exploring these questions using FairML, a new Python library that audits black-box predictive models.
Fast iteration wins prizes
Great Quora answer on “Why has Keras been so successful lately at Kaggle competitions?” (By the author of Keras, an open source neural net library designed to enable fast experimentation). Key quote: ”You don’t lose to people who are smarter than you, you lose to people who have iterated through more experiments than you did, refining their models a little bit each time. If you ranked teams on Kaggle by how many experiments they ran, I’m sure you would see a very strong correlation with the final competition leaderboard.”
Language from police body camera footage shows racial disparities in officer respect
This paper presents a systematic analysis of officer body-worn camera footage, using computational linguistic techniques to automatically measure the respect level that officers display to community members.
Large-scale brainlike systems are possible with existing technology — if we’re willing to spend the money — proposes Jennifer Hassler in A Road Map for the Artificial Brain.
Pretty well re-tweeted and shared already, but interesting nonetheless: External cognition: The Thoughts of a Spiderweb.
And related somewhat related (or at least a really nice AR UX for controlling synthesizers), a demonstration of “prosthetic knowledge” — check out the two minute video with sound at the bottom of the page – awesome stuff!
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